------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  ...\1903 JOP\law_da.log
  log type:  text
 opened on:  12 Mar 2019, 13:28:56

. 
. set seed Xf247741de86536d3b7894a790591f96500044064

. 
. ologit law_da lawendorse ///
>      saccounty sac_lawendorse ///
>          black black_lawendorse

Iteration 0:   log likelihood = -2054.4789  
Iteration 1:   log likelihood = -2041.2242  
Iteration 2:   log likelihood =  -2041.214  
Iteration 3:   log likelihood =  -2041.214  

Ordered logistic regression                       Number of obs   =       1917
                                                  LR chi2(5)      =      26.53
                                                  Prob > chi2     =     0.0001
Log likelihood =  -2041.214                       Pseudo R2       =     0.0065

----------------------------------------------------------------------------------
          law_da |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
      lawendorse |    .052588   .1279622     0.41   0.681    -.1982133    .3033892
       saccounty |   .2286457   .1179817     1.94   0.053    -.0025943    .4598857
  sac_lawendorse |   .2341139   .1707774     1.37   0.170    -.1006036    .5688314
           black |  -.1646507   .2077962    -0.79   0.428    -.5719237    .2426224
black_lawendorse |  -.3845938    .317681    -1.21   0.226    -1.007237    .2380495
-----------------+----------------------------------------------------------------
           /cut1 |     -1.044   .0942515                      -1.22873   -.8592708
           /cut2 |   .7158295   .0923271                      .5348717    .8967873
----------------------------------------------------------------------------------

. 
. estsimp ologit law_da lawendorse ///
>      saccounty sac_lawendorse ///
>          black black_lawendorse

Iteration 0:   log likelihood = -2054.4789
Iteration 1:   log likelihood = -2041.2242
Iteration 2:   log likelihood =  -2041.214

Ordered logit estimates                           Number of obs   =       1917
                                                  LR chi2(5)      =      26.53
                                                  Prob > chi2     =     0.0001
Log likelihood =  -2041.214                       Pseudo R2       =     0.0065

------------------------------------------------------------------------------
      law_da |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  lawendorse |    .052588   .1279618     0.41   0.681    -.1982126    .3033885
   saccounty |   .2286457   .1179814     1.94   0.053    -.0025936     .459885
sac_lawend~e |   .2341139   .1707769     1.37   0.170    -.1006027    .5688305
       black |  -.1646507   .2077956    -0.79   0.428    -.5719225    .2426212
black_lawe~e |  -.3845938   .3176801    -1.21   0.226    -1.007235    .2380477
-------------+----------------------------------------------------------------
       _cut1 |     -1.044   .0942511          (Ancillary parameters)
       _cut2 |   .7158295   .0923268 
------------------------------------------------------------------------------

Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7

. 
. 
. * Control group, non-Sac
. 
. setx median

. setx lawendorse 0

. simqi, prval(3) genpr(control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         1       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |    .381374     .0212459     .3404309    .4247407

Simqi generated the following new variable(s): control_pr

. 
. simqi, fd(prval(3) genpr(lawendorse_fd)) changex(lawendorse 0 1)

First Difference: lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(law_da = 3) |   .0140052     .0317225    -.0465919    .0762904

Simqi generated the following new variable(s): lawendorse_fd

. 
. 
. * Endorsement Treatment group, non-Sac
. 
. setx lawendorse 1

. simqi, prval(3) genpr(lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         1         1     
  sac_lawendorse |         0       median  
       saccounty |         1       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |   .3953793     .0378158     .3231485    .4734834

Simqi generated the following new variable(s): lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
  control_pr |   .381374  .0212459  .3114781  .3480423  .3544845  .3807408  .4081567  .4180496  .4436487
--------------------------------------------------------------------------------------------------------

. tabstat lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
lawendorse~r |  .3953793  .0378158  .2896463  .3333605  .3471423  .3943393  .4458429  .4626867  .5182238
--------------------------------------------------------------------------------------------------------

. 
. gen dif_con_law_pr = lawendorse_pr - control_pr
(1759 missing values generated)

. 
. tabstat dif_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_con_la~r |  .0140052  .0317225 -.0767163 -.0356105 -.0263905  .0127959  .0569485  .0675141  .1050822
--------------------------------------------------------------------------------------------------------

. 
. 
. * Control group, Sac
. 
. setx median

. setx saccounty 1

. setx lawendorse 0

. simqi, prval(3) genpr(sac_control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         1         1     
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |    .381374     .0212459     .3404309    .4247407

Simqi generated the following new variable(s): sac_control_pr

. 
. simqi, fd(prval(3) genpr(sac_lawendorse_fd)) changex(lawendorse 0 1 sac_lawendorse 0 1)

First Difference: lawendorse 0 1 sac_lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(law_da = 3) |   .0680457     .0298325     .0101922    .1288764

Simqi generated the following new variable(s): sac_lawendorse_fd

. 
. 
. * Endorsement Treatment group, Sac
. 
. setx lawendorse 1

. setx sac_lawendorse 1

. simqi, prval(3) genpr(sac_lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         0       median  
black_lawendorse |         0       median  
      lawendorse |         1         1     
  sac_lawendorse |         1         1     
       saccounty |         1         1     
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |   .4494197     .0210732     .4105718    .4918529

Simqi generated the following new variable(s): sac_lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat sac_control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_contro~r |   .381374  .0212459  .3114781  .3480423  .3544845  .3807408  .4081567  .4180496  .4436487
--------------------------------------------------------------------------------------------------------

. tabstat sac_lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_lawend~r |  .4494197  .0210732  .3748078  .4153019  .4222759  .4495013  .4763113  .4843264  .5235015
--------------------------------------------------------------------------------------------------------

. 
. gen dif_sac_con_law_pr = sac_lawendorse_pr - sac_control_pr
(1759 missing values generated)

. 
. tabstat dif_sac_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_sac_co~r |  .0680457  .0298325 -.0278204  .0167882  .0303918  .0682793  .1068659  .1174856  .1619461
--------------------------------------------------------------------------------------------------------

. 
. 
. * Control group, Black
. 
. setx median

. setx black 1

. setx lawendorse 0

. simqi, prval(3) genpr(black_control_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         1         1     
black_lawendorse |         0       median  
      lawendorse |         0         0     
  sac_lawendorse |         0       median  
       saccounty |         1       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |   .3445723     .0464467     .2579846    .4330537

Simqi generated the following new variable(s): black_control_pr

. 
. simqi, fd(prval(3) genpr(black_lawendorse_fd)) changex(lawendorse 0 1 black_lawendorse 0 1)

First Difference: lawendorse 0 1 black_lawendorse 0 1

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(law_da = 3) |  -.0691753     .0664574    -.1957698    .0599184

Simqi generated the following new variable(s): black_lawendorse_fd

. 
. 
. * Endorsement Treatment group, Sac
. 
. setx lawendorse 1

. setx black_lawendorse 1

. simqi, prval(3) genpr(black_lawendorse_pr) listx

You have set the following values for the explanatory variables:

-------------------------------------------
        Variable |    Value     Description
-----------------+-------------------------
           black |         1         1     
black_lawendorse |         1         1     
      lawendorse |         1         1     
  sac_lawendorse |         0       median  
       saccounty |         1       median  
-------------------------------------------


Quantities of interest based on those explanatory values:

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
              Pr(law_da=3) |    .275397     .0541783     .1779357    .3919437

Simqi generated the following new variable(s): black_lawendorse_pr

. 
. 
. * Difference in baseline probabilities
. 
. tabstat black_control_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_cont~r |  .3445723  .0464467  .2222487  .2730874  .2848727  .3445523  .4084079  .4246799  .4802847
--------------------------------------------------------------------------------------------------------

. tabstat black_lawendorse_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_lawe~r |   .275397  .0541783  .1247245  .1924325  .2059767  .2720768  .3479124   .369152  .4622076
--------------------------------------------------------------------------------------------------------

. 
. gen dif_black_con_law_pr = black_lawendorse_pr - black_control_pr
(1759 missing values generated)

. 
. tabstat dif_black_con_law_pr, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_black_~r | -.0691753  .0664574  -.234291 -.1747095 -.1548532 -.0706501  .0141973  .0411202  .1821209
--------------------------------------------------------------------------------------------------------

. 
. 
. * Calculate difference in first differences
. 
. tabstat lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
lawendorse~d |  .0140052  .0317225 -.0767163 -.0356105 -.0263905  .0127959  .0569485  .0675141  .1050822
--------------------------------------------------------------------------------------------------------

. tabstat sac_lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
sac_lawend~d |  .0680457  .0298325 -.0278204  .0167882  .0303918  .0682793  .1068659  .1174856  .1619461
--------------------------------------------------------------------------------------------------------

. tabstat black_lawendorse_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
black_lawe~d | -.0691753  .0664574  -.234291 -.1747095 -.1548532 -.0706501  .0141973  .0411202  .1821209
--------------------------------------------------------------------------------------------------------

. 
. gen dif_sac_non_law_fd = sac_lawendorse_fd - lawendorse_fd
(1759 missing values generated)

. gen dif_black_non_law_fd = black_lawendorse_fd - lawendorse_fd
(1759 missing values generated)

. gen dif_black_sac_law_fd = black_lawendorse_fd - sac_lawendorse_fd
(1759 missing values generated)

. 
. tabstat dif_sac_non_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_sac_no~d |  .0540404  .0421932  -.082529 -.0159089  .0003255  .0549468  .1049605  .1226383   .172759
--------------------------------------------------------------------------------------------------------

. tabstat dif_black_non_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif_black_n~ | -.0831806  .0668004 -.3144754   -.19066 -.1698554 -.0834469  .0033028  .0253292  .1376913
--------------------------------------------------------------------------------------------------------

. tabstat dif_black_sac_law_fd, s(mean sd min p5 p10 p50 p90 p95 max)

    variable |      mean        sd       min        p5       p10       p50       p90       p95       max
-------------+------------------------------------------------------------------------------------------
dif~c_law_fd |  -.137221  .0760858 -.3513066 -.2578394 -.2349182 -.1374787 -.0391035 -.0117366  .1211416
--------------------------------------------------------------------------------------------------------

. 
. 
. drop b1-b7

. drop control_pr-dif_black_sac_law_fd

. 
. log close
      name:  <unnamed>
       log:  ...\1903 JOP\law_da.log
  log type:  text
 closed on:  12 Mar 2019, 13:28:57
------------------------------------------------------------------------------------------------------------
